{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:57:24Z","timestamp":1754157444379,"version":"3.41.2"},"reference-count":8,"publisher":"Emerald","issue":"9\/10","license":[{"start":{"date-parts":[[2008,10,17]],"date-time":"2008-10-17T00:00:00Z","timestamp":1224201600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,10,17]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The traditional method to distinguish the serotype of influenza A virus was based on the antigen reaction of HA and NA with their antibodies. The antibody of specific subtype virus was difficult to get and the reaction was not easy to be done. To be a complementation to the traditional classification methods based on the serological reaction, aims to present a novel method for viral classification.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>The similarity values of all subtype HA genes in vector space were considered and classified using a probabilistic neural network (PNN). The PNN model was trained by the 132 viral sequences in the training set and the classification quality was examined using 28 viral sequences in the testing set.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>A novel technique for the serotype classification of influenza A virus isolated from human was proposed in the paper. The system achieved 100 per cent accuracy with all serotypes of human influenza A virus.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>The time for the large\u2010scale calculations of the average similarity based on multisequence alignment is the main limitation.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>This is a supplementation to the traditional virology research.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The novel classification method based on the similarity of viral nucleotide sequences and the PNN model would be useful for the epidemic supervision and prevention.<\/jats:p><\/jats:sec>","DOI":"10.1108\/03684920810907733","type":"journal-article","created":{"date-parts":[[2008,10,25]],"date-time":"2008-10-25T07:12:58Z","timestamp":1224918778000},"page":"1425-1430","source":"Crossref","is-referenced-by-count":1,"title":["Human influenza: a virus classification using a probabilistic neural network"],"prefix":"10.1108","volume":"37","author":[{"given":"Zheng","family":"Kou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanhong","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoli","family":"Qiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022020819554194700_b2","doi-asserted-by":"crossref","unstructured":"Charles, J. and Robert, G.W. 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(2003), \u201cShort\u2010term load forecasting by artificial neural network integrated with fuzzy logic\u201d, Advances in Systems Science and Applications, Vol. 3, pp. 398\u2010404."}],"container-title":["Kybernetes"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/03684920810907733","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/03684920810907733\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/03684920810907733\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:53:25Z","timestamp":1753401205000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/k\/article\/37\/9-10\/1425-1430\/459673"}},"subtitle":[],"editor":[{"given":"Mian\u2010yun","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2008,10,17]]},"references-count":8,"journal-issue":{"issue":"9\/10","published-print":{"date-parts":[[2008,10,17]]}},"alternative-id":["10.1108\/03684920810907733"],"URL":"https:\/\/doi.org\/10.1108\/03684920810907733","relation":{},"ISSN":["0368-492X"],"issn-type":[{"type":"print","value":"0368-492X"}],"subject":[],"published":{"date-parts":[[2008,10,17]]}}}